Triple

T17245900
Position Surface form Disambiguated ID Type / Status
Subject Notting Hill E418623 entity
Predicate adjacentTo P224 FINISHED
Object Kensington E14419 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Kensington | Statement: [Notting Hill, adjacentTo, Kensington]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kensington
Context triple: [Notting Hill, adjacentTo, Kensington]
  • A. Kensington
    Kensington is a historic Philadelphia neighborhood known for its industrial past and ongoing urban redevelopment.
  • B. Kensington chosen
    Kensington is a district in West London, England, known for its affluent residential areas, cultural institutions, and royal associations.
  • C. Kensington
    Kensington is an inner-city suburb of Sydney, Australia, known for hosting the main campus of the University of New South Wales.
  • D. Kensington
    Kensington is a small, affluent residential village located on the North Shore of Long Island in Nassau County, New York.
  • E. Kensington
    Kensington is an inner-city suburb of Melbourne, Victoria, known for its mix of historic workers’ cottages, industrial heritage, and growing residential developments close to the central business district.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d886d8e96081909870bff6c3d0bf09 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42e23b8948190870d0e6b4e55b4e3 completed April 19, 2026, 1:21 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170dd38708190b17cee0ab6cee6eb completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:39 a.m.